Overview

Dataset statistics

Number of variables23
Number of observations2002
Missing cells0
Missing cells (%)0.0%
Duplicate rows999
Duplicate rows (%)49.9%
Total size in memory359.9 KiB
Average record size in memory184.1 B

Variable types

Numeric21
Categorical2

Alerts

Dataset has 999 (49.9%) duplicate rowsDuplicates
PAY_0 is highly overall correlated with PAY_2 and 4 other fieldsHigh correlation
PAY_2 is highly overall correlated with PAY_0 and 4 other fieldsHigh correlation
PAY_3 is highly overall correlated with PAY_0 and 4 other fieldsHigh correlation
PAY_4 is highly overall correlated with PAY_0 and 4 other fieldsHigh correlation
PAY_5 is highly overall correlated with PAY_0 and 4 other fieldsHigh correlation
PAY_6 is highly overall correlated with PAY_0 and 4 other fieldsHigh correlation
BILL_AMT1 is highly overall correlated with LIMIT_BAL and 5 other fieldsHigh correlation
BILL_AMT2 is highly overall correlated with LIMIT_BAL and 5 other fieldsHigh correlation
BILL_AMT3 is highly overall correlated with LIMIT_BAL and 5 other fieldsHigh correlation
BILL_AMT4 is highly overall correlated with LIMIT_BAL and 6 other fieldsHigh correlation
BILL_AMT5 is highly overall correlated with BILL_AMT1 and 4 other fieldsHigh correlation
BILL_AMT6 is highly overall correlated with BILL_AMT1 and 4 other fieldsHigh correlation
PAY_AMT1 is highly overall correlated with PAY_AMT6High correlation
PAY_AMT2 is highly overall correlated with PAY_AMT5 and 1 other fieldsHigh correlation
PAY_AMT3 is highly overall correlated with BILL_AMT4High correlation
PAY_AMT4 is highly overall correlated with BILL_AMT4High correlation
PAY_AMT5 is highly overall correlated with PAY_AMT2High correlation
PAY_AMT6 is highly overall correlated with PAY_AMT1 and 1 other fieldsHigh correlation
LIMIT_BAL is highly overall correlated with BILL_AMT1 and 3 other fieldsHigh correlation
PAY_0 has 949 (47.4%) zerosZeros
PAY_2 has 1053 (52.6%) zerosZeros
PAY_3 has 1028 (51.3%) zerosZeros
PAY_4 has 1080 (53.9%) zerosZeros
PAY_5 has 1088 (54.3%) zerosZeros
PAY_6 has 1001 (50.0%) zerosZeros
BILL_AMT1 has 148 (7.4%) zerosZeros
BILL_AMT2 has 198 (9.9%) zerosZeros
BILL_AMT3 has 224 (11.2%) zerosZeros
BILL_AMT4 has 261 (13.0%) zerosZeros
BILL_AMT5 has 273 (13.6%) zerosZeros
BILL_AMT6 has 307 (15.3%) zerosZeros
PAY_AMT1 has 365 (18.2%) zerosZeros
PAY_AMT2 has 408 (20.4%) zerosZeros
PAY_AMT3 has 449 (22.4%) zerosZeros
PAY_AMT4 has 463 (23.1%) zerosZeros
PAY_AMT5 has 472 (23.6%) zerosZeros
PAY_AMT6 has 546 (27.3%) zerosZeros

Reproduction

Analysis started2023-02-23 14:45:15.489168
Analysis finished2023-02-23 14:46:03.804379
Duration48.32 seconds
Software versionpandas-profiling vv3.5.0
Download configurationconfig.json

Variables

LIMIT_BAL
Real number (ℝ)

Distinct56
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167087.91
Minimum10000
Maximum700000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:03.883169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile20000
Q150000
median140000
Q3240000
95-th percentile420000
Maximum700000
Range690000
Interquartile range (IQR)190000

Descriptive statistics

Standard deviation130519.9
Coefficient of variation (CV)0.78114506
Kurtosis0.55443325
Mean167087.91
Median Absolute Deviation (MAD)90000
Skewness1.0165149
Sum3.3451 × 108
Variance1.7035444 × 1010
MonotonicityNot monotonic
2023-02-23T20:46:04.012191image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 260
 
13.0%
20000 117
 
5.8%
30000 114
 
5.7%
200000 103
 
5.1%
80000 88
 
4.4%
180000 72
 
3.6%
360000 68
 
3.4%
100000 66
 
3.3%
140000 64
 
3.2%
60000 58
 
2.9%
Other values (46) 992
49.6%
ValueCountFrequency (%)
10000 26
 
1.3%
20000 117
5.8%
30000 114
5.7%
40000 20
 
1.0%
50000 260
13.0%
60000 58
 
2.9%
70000 46
 
2.3%
80000 88
 
4.4%
90000 51
 
2.5%
100000 66
 
3.3%
ValueCountFrequency (%)
700000 2
 
0.1%
630000 4
 
0.2%
620000 2
 
0.1%
610000 2
 
0.1%
600000 2
 
0.1%
580000 2
 
0.1%
510000 4
 
0.2%
500000 44
2.2%
490000 4
 
0.2%
480000 4
 
0.2%

SEX
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
2
1182 
1
820 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2002
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 1182
59.0%
1 820
41.0%

Length

2023-02-23T20:46:04.128682image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-23T20:46:04.227626image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
2 1182
59.0%
1 820
41.0%

Most occurring characters

ValueCountFrequency (%)
2 1182
59.0%
1 820
41.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2002
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1182
59.0%
1 820
41.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2002
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1182
59.0%
1 820
41.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1182
59.0%
1 820
41.0%

EDUCATION
Real number (ℝ)

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7762238
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:04.301976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile3
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.74939531
Coefficient of variation (CV)0.42190366
Kurtosis1.7330872
Mean1.7762238
Median Absolute Deviation (MAD)1
Skewness0.87584311
Sum3556
Variance0.56159333
MonotonicityNot monotonic
2023-02-23T20:46:04.382131image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 898
44.9%
1 790
39.5%
3 300
 
15.0%
5 6
 
0.3%
4 4
 
0.2%
6 4
 
0.2%
ValueCountFrequency (%)
1 790
39.5%
2 898
44.9%
3 300
 
15.0%
4 4
 
0.2%
5 6
 
0.3%
6 4
 
0.2%
ValueCountFrequency (%)
6 4
 
0.2%
5 6
 
0.3%
4 4
 
0.2%
3 300
 
15.0%
2 898
44.9%
1 790
39.5%

MARRIAGE
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
2
1139 
1
819 
3
 
38
0
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2002
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 1139
56.9%
1 819
40.9%
3 38
 
1.9%
0 6
 
0.3%

Length

2023-02-23T20:46:04.473254image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-23T20:46:04.577243image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
ValueCountFrequency (%)
2 1139
56.9%
1 819
40.9%
3 38
 
1.9%
0 6
 
0.3%

Most occurring characters

ValueCountFrequency (%)
2 1139
56.9%
1 819
40.9%
3 38
 
1.9%
0 6
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2002
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1139
56.9%
1 819
40.9%
3 38
 
1.9%
0 6
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2002
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1139
56.9%
1 819
40.9%
3 38
 
1.9%
0 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1139
56.9%
1 819
40.9%
3 38
 
1.9%
0 6
 
0.3%

AGE
Real number (ℝ)

Distinct44
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.941059
Minimum21
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:04.680400image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile23
Q128
median33
Q341
95-th percentile53
Maximum75
Range54
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.2197625
Coefficient of variation (CV)0.26386614
Kurtosis0.23296966
Mean34.941059
Median Absolute Deviation (MAD)6
Skewness0.81664579
Sum69952
Variance85.00402
MonotonicityNot monotonic
2023-02-23T20:46:04.806676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
29 114
 
5.7%
27 114
 
5.7%
34 96
 
4.8%
28 95
 
4.7%
30 94
 
4.7%
32 92
 
4.6%
24 87
 
4.3%
26 83
 
4.1%
31 78
 
3.9%
25 74
 
3.7%
Other values (34) 1075
53.7%
ValueCountFrequency (%)
21 2
 
0.1%
22 54
2.7%
23 70
3.5%
24 87
4.3%
25 74
3.7%
26 83
4.1%
27 114
5.7%
28 95
4.7%
29 114
5.7%
30 94
4.7%
ValueCountFrequency (%)
75 2
 
0.1%
73 2
 
0.1%
63 2
 
0.1%
61 2
 
0.1%
60 6
 
0.3%
59 6
 
0.3%
58 12
0.6%
57 12
0.6%
56 20
1.0%
55 14
0.7%

PAY_0
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.002997003
Minimum-2
Maximum8
Zeros949
Zeros (%)47.4%
Negative586
Negative (%)29.3%
Memory size15.8 KiB
2023-02-23T20:46:04.909397image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum8
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1718807
Coefficient of variation (CV)-391.01752
Kurtosis8.0908004
Mean-0.002997003
Median Absolute Deviation (MAD)1
Skewness1.5146319
Sum-6
Variance1.3733044
MonotonicityNot monotonic
2023-02-23T20:46:04.991909image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 949
47.4%
-1 428
21.4%
1 272
 
13.6%
2 167
 
8.3%
-2 158
 
7.9%
3 12
 
0.6%
4 8
 
0.4%
8 8
 
0.4%
ValueCountFrequency (%)
-2 158
 
7.9%
-1 428
21.4%
0 949
47.4%
1 272
 
13.6%
2 167
 
8.3%
3 12
 
0.6%
4 8
 
0.4%
8 8
 
0.4%
ValueCountFrequency (%)
8 8
 
0.4%
4 8
 
0.4%
3 12
 
0.6%
2 167
 
8.3%
1 272
 
13.6%
0 949
47.4%
-1 428
21.4%
-2 158
 
7.9%

PAY_2
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.15534466
Minimum-2
Maximum7
Zeros1053
Zeros (%)52.6%
Negative671
Negative (%)33.5%
Memory size15.8 KiB
2023-02-23T20:46:05.074688image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum7
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2274325
Coefficient of variation (CV)-7.9013502
Kurtosis4.3142633
Mean-0.15534466
Median Absolute Deviation (MAD)0
Skewness1.2068973
Sum-311
Variance1.5065906
MonotonicityNot monotonic
2023-02-23T20:46:05.152478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1053
52.6%
-1 411
 
20.5%
-2 260
 
13.0%
2 248
 
12.4%
3 16
 
0.8%
7 8
 
0.4%
5 2
 
0.1%
4 2
 
0.1%
1 2
 
0.1%
ValueCountFrequency (%)
-2 260
 
13.0%
-1 411
 
20.5%
0 1053
52.6%
1 2
 
0.1%
2 248
 
12.4%
3 16
 
0.8%
4 2
 
0.1%
5 2
 
0.1%
7 8
 
0.4%
ValueCountFrequency (%)
7 8
 
0.4%
5 2
 
0.1%
4 2
 
0.1%
3 16
 
0.8%
2 248
 
12.4%
1 2
 
0.1%
0 1053
52.6%
-1 411
 
20.5%
-2 260
 
13.0%

PAY_3
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.16083916
Minimum-2
Maximum7
Zeros1028
Zeros (%)51.3%
Negative690
Negative (%)34.5%
Memory size15.8 KiB
2023-02-23T20:46:05.236227image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum7
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2594887
Coefficient of variation (CV)-7.830734
Kurtosis3.9731707
Mean-0.16083916
Median Absolute Deviation (MAD)0
Skewness1.2303656
Sum-322
Variance1.5863117
MonotonicityNot monotonic
2023-02-23T20:46:05.313752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1028
51.3%
-1 416
20.8%
-2 274
 
13.7%
2 258
 
12.9%
4 8
 
0.4%
6 8
 
0.4%
7 4
 
0.2%
3 2
 
0.1%
1 2
 
0.1%
5 2
 
0.1%
ValueCountFrequency (%)
-2 274
 
13.7%
-1 416
20.8%
0 1028
51.3%
1 2
 
0.1%
2 258
 
12.9%
3 2
 
0.1%
4 8
 
0.4%
5 2
 
0.1%
6 8
 
0.4%
7 4
 
0.2%
ValueCountFrequency (%)
7 4
 
0.2%
6 8
 
0.4%
5 2
 
0.1%
4 8
 
0.4%
3 2
 
0.1%
2 258
 
12.9%
1 2
 
0.1%
0 1028
51.3%
-1 416
20.8%
-2 274
 
13.7%

PAY_4
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.27972028
Minimum-2
Maximum7
Zeros1080
Zeros (%)53.9%
Negative720
Negative (%)36.0%
Memory size15.8 KiB
2023-02-23T20:46:05.396533image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum7
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.181939
Coefficient of variation (CV)-4.225432
Kurtosis4.4573116
Mean-0.27972028
Median Absolute Deviation (MAD)0
Skewness1.219633
Sum-560
Variance1.3969798
MonotonicityNot monotonic
2023-02-23T20:46:05.473297image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1080
53.9%
-1 408
 
20.4%
-2 312
 
15.6%
2 174
 
8.7%
3 10
 
0.5%
5 10
 
0.5%
4 4
 
0.2%
7 4
 
0.2%
ValueCountFrequency (%)
-2 312
 
15.6%
-1 408
 
20.4%
0 1080
53.9%
2 174
 
8.7%
3 10
 
0.5%
4 4
 
0.2%
5 10
 
0.5%
7 4
 
0.2%
ValueCountFrequency (%)
7 4
 
0.2%
5 10
 
0.5%
4 4
 
0.2%
3 10
 
0.5%
2 174
 
8.7%
0 1080
53.9%
-1 408
 
20.4%
-2 312
 
15.6%

PAY_5
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.28021978
Minimum-2
Maximum7
Zeros1088
Zeros (%)54.3%
Negative708
Negative (%)35.4%
Memory size15.8 KiB
2023-02-23T20:46:05.555395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum7
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1679967
Coefficient of variation (CV)-4.168145
Kurtosis3.75307
Mean-0.28021978
Median Absolute Deviation (MAD)0
Skewness1.0535828
Sum-561
Variance1.3642162
MonotonicityNot monotonic
2023-02-23T20:46:05.631222image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1088
54.3%
-1 387
 
19.3%
-2 321
 
16.0%
2 180
 
9.0%
3 10
 
0.5%
4 10
 
0.5%
7 4
 
0.2%
5 2
 
0.1%
ValueCountFrequency (%)
-2 321
 
16.0%
-1 387
 
19.3%
0 1088
54.3%
2 180
 
9.0%
3 10
 
0.5%
4 10
 
0.5%
5 2
 
0.1%
7 4
 
0.2%
ValueCountFrequency (%)
7 4
 
0.2%
5 2
 
0.1%
4 10
 
0.5%
3 10
 
0.5%
2 180
 
9.0%
0 1088
54.3%
-1 387
 
19.3%
-2 321
 
16.0%

PAY_6
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.31018981
Minimum-2
Maximum7
Zeros1001
Zeros (%)50.0%
Negative778
Negative (%)38.9%
Memory size15.8 KiB
2023-02-23T20:46:05.712795image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile-2
Q1-1
median0
Q30
95-th percentile2
Maximum7
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2022742
Coefficient of variation (CV)-3.8759308
Kurtosis3.3173686
Mean-0.31018981
Median Absolute Deviation (MAD)0.5
Skewness1.0622789
Sum-621
Variance1.4454633
MonotonicityNot monotonic
2023-02-23T20:46:05.789590image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1001
50.0%
-1 435
21.7%
-2 343
 
17.1%
2 197
 
9.8%
3 16
 
0.8%
6 6
 
0.3%
4 2
 
0.1%
7 2
 
0.1%
ValueCountFrequency (%)
-2 343
 
17.1%
-1 435
21.7%
0 1001
50.0%
2 197
 
9.8%
3 16
 
0.8%
4 2
 
0.1%
6 6
 
0.3%
7 2
 
0.1%
ValueCountFrequency (%)
7 2
 
0.1%
6 6
 
0.3%
4 2
 
0.1%
3 16
 
0.8%
2 197
 
9.8%
0 1001
50.0%
-1 435
21.7%
-2 343
 
17.1%

BILL_AMT1
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct907
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49422.346
Minimum-14386
Maximum507726
Zeros148
Zeros (%)7.4%
Negative44
Negative (%)2.2%
Memory size15.8 KiB
2023-02-23T20:46:05.893312image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-14386
5-th percentile0
Q13136
median21229
Q359801.75
95-th percentile199436
Maximum507726
Range522112
Interquartile range (IQR)56665.75

Descriptive statistics

Standard deviation72613.583
Coefficient of variation (CV)1.469246
Kurtosis8.9570767
Mean49422.346
Median Absolute Deviation (MAD)20831.5
Skewness2.6708569
Sum98943537
Variance5.2727324 × 109
MonotonicityNot monotonic
2023-02-23T20:46:06.023763image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 148
 
7.4%
390 16
 
0.8%
780 8
 
0.4%
396 6
 
0.3%
316 6
 
0.3%
5780 4
 
0.2%
2000 4
 
0.2%
819 4
 
0.2%
-200 4
 
0.2%
650 4
 
0.2%
Other values (897) 1798
89.8%
ValueCountFrequency (%)
-14386 2
0.1%
-2000 2
0.1%
-1312 2
0.1%
-1100 2
0.1%
-946 2
0.1%
-709 2
0.1%
-475 2
0.1%
-288 2
0.1%
-200 4
0.2%
-190 2
0.1%
ValueCountFrequency (%)
507726 2
0.1%
507062 2
0.1%
471814 2
0.1%
467150 2
0.1%
422069 2
0.1%
400134 2
0.1%
386405 2
0.1%
367965 2
0.1%
366193 2
0.1%
355215 2
0.1%

BILL_AMT2
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct878
Distinct (%)43.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47891.357
Minimum-13543
Maximum509229
Zeros198
Zeros (%)9.9%
Negative47
Negative (%)2.3%
Memory size15.8 KiB
2023-02-23T20:46:06.149427image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-13543
5-th percentile0
Q13275.5
median20408.5
Q358417.75
95-th percentile196143
Maximum509229
Range522772
Interquartile range (IQR)55142.25

Descriptive statistics

Standard deviation72055.49
Coefficient of variation (CV)1.5045615
Kurtosis9.6659181
Mean47891.357
Median Absolute Deviation (MAD)20092.5
Skewness2.7766944
Sum95878497
Variance5.1919937 × 109
MonotonicityNot monotonic
2023-02-23T20:46:06.777301image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 198
 
9.9%
390 10
 
0.5%
780 8
 
0.4%
316 8
 
0.4%
300 8
 
0.4%
396 6
 
0.3%
-200 6
 
0.3%
1261 6
 
0.3%
291 6
 
0.3%
100 4
 
0.2%
Other values (868) 1742
87.0%
ValueCountFrequency (%)
-13543 2
0.1%
-9850 2
0.1%
-1100 2
0.1%
-1041 2
0.1%
-946 2
0.1%
-818 1
< 0.1%
-709 2
0.1%
-707 2
0.1%
-425 2
0.1%
-303 2
0.1%
ValueCountFrequency (%)
509229 2
0.1%
491956 2
0.1%
478380 2
0.1%
458862 2
0.1%
431342 2
0.1%
412023 2
0.1%
398857 2
0.1%
387910 2
0.1%
372700 2
0.1%
363325 2
0.1%

BILL_AMT3
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct866
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44981.964
Minimum-9850
Maximum499936
Zeros224
Zeros (%)11.2%
Negative44
Negative (%)2.2%
Memory size15.8 KiB
2023-02-23T20:46:06.904085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-9850
5-th percentile0
Q11947
median19298
Q354477
95-th percentile186292
Maximum499936
Range509786
Interquartile range (IQR)52530

Descriptive statistics

Standard deviation69510.626
Coefficient of variation (CV)1.5452999
Kurtosis10.605545
Mean44981.964
Median Absolute Deviation (MAD)18908
Skewness2.8994823
Sum90053892
Variance4.8317271 × 109
MonotonicityNot monotonic
2023-02-23T20:46:07.031574image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 224
 
11.2%
390 16
 
0.8%
396 6
 
0.3%
316 6
 
0.3%
-2 6
 
0.3%
780 6
 
0.3%
664 4
 
0.2%
325 4
 
0.2%
1350 4
 
0.2%
13001 4
 
0.2%
Other values (856) 1722
86.0%
ValueCountFrequency (%)
-9850 2
0.1%
-2697 2
0.1%
-1690 2
0.1%
-946 2
0.1%
-709 2
0.1%
-684 2
0.1%
-527 2
0.1%
-387 2
0.1%
-288 2
0.1%
-281 2
0.1%
ValueCountFrequency (%)
499936 2
0.1%
479432 2
0.1%
469703 2
0.1%
445007 2
0.1%
430637 2
0.1%
404205 2
0.1%
395612 2
0.1%
375948 2
0.1%
375070 2
0.1%
373181 2
0.1%

BILL_AMT4
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct848
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40741.321
Minimum-3684
Maximum628699
Zeros261
Zeros (%)13.0%
Negative44
Negative (%)2.2%
Memory size15.8 KiB
2023-02-23T20:46:07.158231image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-3684
5-th percentile0
Q11438
median17743
Q348800
95-th percentile167163
Maximum628699
Range632383
Interquartile range (IQR)47362

Descriptive statistics

Standard deviation68166.982
Coefficient of variation (CV)1.6731657
Kurtosis17.846334
Mean40741.321
Median Absolute Deviation (MAD)17328
Skewness3.5793917
Sum81564124
Variance4.6467374 × 109
MonotonicityNot monotonic
2023-02-23T20:46:07.284215image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 261
 
13.0%
390 14
 
0.7%
316 10
 
0.5%
300 6
 
0.3%
2340 4
 
0.2%
362 4
 
0.2%
5400 4
 
0.2%
240 4
 
0.2%
5818 4
 
0.2%
-2 4
 
0.2%
Other values (838) 1687
84.3%
ValueCountFrequency (%)
-3684 2
0.1%
-2898 2
0.1%
-2618 2
0.1%
-946 2
0.1%
-923 2
0.1%
-828 2
0.1%
-810 2
0.1%
-387 2
0.1%
-288 2
0.1%
-281 2
0.1%
ValueCountFrequency (%)
628699 2
0.1%
542653 2
0.1%
505507 2
0.1%
487066 2
0.1%
479978 2
0.1%
447130 2
0.1%
386295 2
0.1%
376657 2
0.1%
360199 2
0.1%
354839 2
0.1%

BILL_AMT5
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct836
Distinct (%)41.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39071.871
Minimum-28335
Maximum484612
Zeros273
Zeros (%)13.6%
Negative52
Negative (%)2.6%
Memory size15.8 KiB
2023-02-23T20:46:07.415501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-28335
5-th percentile0
Q11254
median17591.5
Q346361.75
95-th percentile165725
Maximum484612
Range512947
Interquartile range (IQR)45107.75

Descriptive statistics

Standard deviation63062.665
Coefficient of variation (CV)1.614017
Kurtosis12.842305
Mean39071.871
Median Absolute Deviation (MAD)17175.5
Skewness3.1093559
Sum78221886
Variance3.9768997 × 109
MonotonicityNot monotonic
2023-02-23T20:46:07.545233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 273
 
13.6%
390 16
 
0.8%
2000 6
 
0.3%
316 6
 
0.3%
396 6
 
0.3%
150 6
 
0.3%
688 4
 
0.2%
19450 4
 
0.2%
166 4
 
0.2%
19323 4
 
0.2%
Other values (826) 1673
83.6%
ValueCountFrequency (%)
-28335 2
0.1%
-5000 2
0.1%
-3272 2
0.1%
-1488 2
0.1%
-1005 2
0.1%
-946 2
0.1%
-783 2
0.1%
-679 2
0.1%
-527 2
0.1%
-420 2
0.1%
ValueCountFrequency (%)
484612 2
0.1%
483003 2
0.1%
471145 2
0.1%
440982 2
0.1%
369532 2
0.1%
356656 2
0.1%
356636 2
0.1%
356206 2
0.1%
335760 2
0.1%
315820 2
0.1%

BILL_AMT6
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct824
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38056.488
Minimum-339603
Maximum473944
Zeros307
Zeros (%)15.3%
Negative36
Negative (%)1.8%
Memory size15.8 KiB
2023-02-23T20:46:07.674171image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-339603
5-th percentile0
Q1869
median15874
Q346557
95-th percentile167964
Maximum473944
Range813547
Interquartile range (IQR)45688

Descriptive statistics

Standard deviation63040.633
Coefficient of variation (CV)1.6565016
Kurtosis12.144814
Mean38056.488
Median Absolute Deviation (MAD)15664.5
Skewness2.635236
Sum76189089
Variance3.9741214 × 109
MonotonicityNot monotonic
2023-02-23T20:46:07.800131image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 307
 
15.3%
390 16
 
0.8%
150 8
 
0.4%
316 8
 
0.4%
291 6
 
0.3%
1320 6
 
0.3%
780 5
 
0.2%
830 4
 
0.2%
199 4
 
0.2%
-200 4
 
0.2%
Other values (814) 1634
81.6%
ValueCountFrequency (%)
-339603 2
0.1%
-3272 2
0.1%
-1884 2
0.1%
-946 2
0.1%
-780 2
0.1%
-304 2
0.1%
-281 2
0.1%
-246 2
0.1%
-200 4
0.2%
-189 2
0.1%
ValueCountFrequency (%)
473944 2
0.1%
469961 2
0.1%
434715 2
0.1%
419643 2
0.1%
367399 2
0.1%
364089 2
0.1%
352257 2
0.1%
330121 2
0.1%
309959 2
0.1%
305498 2
0.1%

PAY_AMT1
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct522
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5373.7023
Minimum0
Maximum199646
Zeros365
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:07.938821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11000
median2160
Q35085
95-th percentile20000
Maximum199646
Range199646
Interquartile range (IQR)4085

Descriptive statistics

Standard deviation12177.441
Coefficient of variation (CV)2.2661175
Kurtosis88.154436
Mean5373.7023
Median Absolute Deviation (MAD)1926
Skewness7.7466708
Sum10758152
Variance1.4829006 × 108
MonotonicityNot monotonic
2023-02-23T20:46:08.068504image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 365
 
18.2%
2000 80
 
4.0%
3000 64
 
3.2%
2500 40
 
2.0%
10000 38
 
1.9%
5000 33
 
1.6%
1000 32
 
1.6%
1500 26
 
1.3%
4000 22
 
1.1%
1800 18
 
0.9%
Other values (512) 1284
64.1%
ValueCountFrequency (%)
0 365
18.2%
1 2
 
0.1%
39 4
 
0.2%
92 2
 
0.1%
100 2
 
0.1%
105 2
 
0.1%
131 2
 
0.1%
138 2
 
0.1%
157 2
 
0.1%
165 2
 
0.1%
ValueCountFrequency (%)
199646 2
0.1%
120093 2
0.1%
120041 2
0.1%
90000 2
0.1%
81690 2
0.1%
80000 4
0.2%
70010 2
0.1%
67650 2
0.1%
57087 2
0.1%
55000 2
0.1%

PAY_AMT2
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct521
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5049.9426
Minimum0
Maximum285138
Zeros408
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:08.203821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1390
median1700
Q34500
95-th percentile16025
Maximum285138
Range285138
Interquartile range (IQR)4110

Descriptive statistics

Standard deviation15622.382
Coefficient of variation (CV)3.0935761
Kurtosis150.69656
Mean5049.9426
Median Absolute Deviation (MAD)1700
Skewness10.744887
Sum10109985
Variance2.4405881 × 108
MonotonicityNot monotonic
2023-02-23T20:46:08.325497image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 408
 
20.4%
2000 57
 
2.8%
1500 54
 
2.7%
5000 54
 
2.7%
3000 54
 
2.7%
1000 49
 
2.4%
1600 24
 
1.2%
1400 20
 
1.0%
1200 20
 
1.0%
6000 18
 
0.9%
Other values (511) 1244
62.1%
ValueCountFrequency (%)
0 408
20.4%
1 2
 
0.1%
2 4
 
0.2%
3 2
 
0.1%
5 2
 
0.1%
7 2
 
0.1%
10 2
 
0.1%
11 2
 
0.1%
12 2
 
0.1%
15 2
 
0.1%
ValueCountFrequency (%)
285138 2
0.1%
199982 2
0.1%
177671 2
0.1%
145000 2
0.1%
104279 2
0.1%
88678 2
0.1%
84440 2
0.1%
75720 2
0.1%
55693 2
0.1%
52110 2
0.1%

PAY_AMT3
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct495
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4130.6553
Minimum0
Maximum133657
Zeros449
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:08.453879image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1229.25
median1200
Q33715
95-th percentile14324.3
Maximum133657
Range133657
Interquartile range (IQR)3485.75

Descriptive statistics

Standard deviation10340.006
Coefficient of variation (CV)2.5032361
Kurtosis61.655392
Mean4130.6553
Median Absolute Deviation (MAD)1200
Skewness6.8182985
Sum8269572
Variance1.0691572 × 108
MonotonicityNot monotonic
2023-02-23T20:46:08.586552image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 449
 
22.4%
1000 103
 
5.1%
2000 76
 
3.8%
3000 70
 
3.5%
5000 44
 
2.2%
1500 24
 
1.2%
6000 20
 
1.0%
10000 20
 
1.0%
500 18
 
0.9%
4000 18
 
0.9%
Other values (485) 1160
57.9%
ValueCountFrequency (%)
0 449
22.4%
3 2
 
0.1%
27 2
 
0.1%
28 2
 
0.1%
50 2
 
0.1%
54 2
 
0.1%
87 2
 
0.1%
91 2
 
0.1%
100 2
 
0.1%
116 2
 
0.1%
ValueCountFrequency (%)
133657 2
0.1%
130000 2
0.1%
89000 1
< 0.1%
80000 2
0.1%
75940 2
0.1%
74354 2
0.1%
68454 2
0.1%
65840 2
0.1%
62520 2
0.1%
61411 2
0.1%

PAY_AMT4
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct482
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4669.7033
Minimum0
Maximum188840
Zeros463
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:08.719235image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1150
median1380
Q34000
95-th percentile17000
Maximum188840
Range188840
Interquartile range (IQR)3850

Descriptive statistics

Standard deviation13266.465
Coefficient of variation (CV)2.8409654
Kurtosis70.355758
Mean4669.7033
Median Absolute Deviation (MAD)1380
Skewness7.4498753
Sum9348746
Variance1.7599911 × 108
MonotonicityNot monotonic
2023-02-23T20:46:08.845488image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 463
23.1%
1000 89
 
4.4%
2000 70
 
3.5%
5000 48
 
2.4%
3000 48
 
2.4%
1500 36
 
1.8%
4000 32
 
1.6%
500 26
 
1.3%
2500 22
 
1.1%
10000 16
 
0.8%
Other values (472) 1152
57.5%
ValueCountFrequency (%)
0 463
23.1%
6 6
 
0.3%
7 2
 
0.1%
17 2
 
0.1%
25 2
 
0.1%
64 2
 
0.1%
69 2
 
0.1%
74 2
 
0.1%
92 2
 
0.1%
98 2
 
0.1%
ValueCountFrequency (%)
188840 2
0.1%
146900 2
0.1%
107591 2
0.1%
100000 4
0.2%
99669 2
0.1%
99000 2
0.1%
97441 2
0.1%
88348 2
0.1%
80552 2
0.1%
79377 2
0.1%

PAY_AMT5
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct481
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5332.6818
Minimum0
Maximum195599
Zeros472
Zeros (%)23.6%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:08.981889image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1196.75
median1306
Q33745
95-th percentile17000
Maximum195599
Range195599
Interquartile range (IQR)3548.25

Descriptive statistics

Standard deviation16807.872
Coefficient of variation (CV)3.151861
Kurtosis58.094076
Mean5332.6818
Median Absolute Deviation (MAD)1306
Skewness7.0296679
Sum10676029
Variance2.8250456 × 108
MonotonicityNot monotonic
2023-02-23T20:46:09.111543image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 472
23.6%
1000 84
 
4.2%
3000 70
 
3.5%
2000 64
 
3.2%
1500 48
 
2.4%
5000 38
 
1.9%
4000 24
 
1.2%
500 18
 
0.9%
1200 16
 
0.8%
3500 16
 
0.8%
Other values (471) 1152
57.5%
ValueCountFrequency (%)
0 472
23.6%
12 2
 
0.1%
60 2
 
0.1%
91 1
 
< 0.1%
100 2
 
0.1%
150 8
 
0.4%
160 2
 
0.1%
162 2
 
0.1%
169 2
 
0.1%
175 2
 
0.1%
ValueCountFrequency (%)
195599 2
 
0.1%
184922 2
 
0.1%
162000 2
 
0.1%
160719 2
 
0.1%
133841 2
 
0.1%
132200 2
 
0.1%
130291 2
 
0.1%
101005 2
 
0.1%
100000 6
0.3%
85900 2
 
0.1%

PAY_AMT6
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct436
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5096.9461
Minimum0
Maximum528666
Zeros546
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2023-02-23T20:46:09.247277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1261
Q33800
95-th percentile13770
Maximum528666
Range528666
Interquartile range (IQR)3800

Descriptive statistics

Standard deviation23652.198
Coefficient of variation (CV)4.6404647
Kurtosis289.2105
Mean5096.9461
Median Absolute Deviation (MAD)1261
Skewness15.230827
Sum10204086
Variance5.5942649 × 108
MonotonicityNot monotonic
2023-02-23T20:46:09.378088image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 546
27.3%
2000 101
 
5.0%
1000 100
 
5.0%
3000 56
 
2.8%
5000 52
 
2.6%
2500 30
 
1.5%
1500 30
 
1.5%
4000 24
 
1.2%
10000 24
 
1.2%
6000 18
 
0.9%
Other values (426) 1021
51.0%
ValueCountFrequency (%)
0 546
27.3%
1 2
 
0.1%
3 2
 
0.1%
4 2
 
0.1%
60 2
 
0.1%
62 2
 
0.1%
66 4
 
0.2%
95 2
 
0.1%
100 4
 
0.2%
102 4
 
0.2%
ValueCountFrequency (%)
528666 2
0.1%
345293 2
0.1%
185652 2
0.1%
167000 2
0.1%
153504 2
0.1%
126685 2
0.1%
105700 2
0.1%
77195 2
0.1%
68978 2
0.1%
67619 2
0.1%

Interactions

2023-02-23T20:46:01.182740image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:16.631346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.898634image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.993172image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.098344image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.183532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.239920image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.282813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.338015image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.379155image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.417655image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.651575image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.804881image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.945013image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.135659image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.282859image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.589348image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.288511image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.418147image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.660488image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.892928image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.290446image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:16.743609image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.004081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.098888image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.203565image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.287251image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.345033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.386563image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.440740image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.482907image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.524939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.761894image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.912250image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.055748image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.243375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.398628image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.705069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.396255image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.530982image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.772216image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.007647image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.388999image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:16.850247image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.100838image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.196712image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.300306image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.381006image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.440346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.481292image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.536484image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.577653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.624240image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.870603image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.011577image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.158479image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.342106image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.507471image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.811785image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.495326image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.635713image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.877338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.114915image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.488733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:16.954730image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.198035image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.304421image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.397614image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.476750image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.535093image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.576064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.629235image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.672436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.721979image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.971888image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.111313image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.260222image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.441842image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.615255image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.917715image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.594030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.739426image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.980629image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.221200image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.586472image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.059478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.295346image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.401170image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.493393image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.570071image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.628845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.670804image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.722985image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.765753image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.820685image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.071132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.210020image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.361899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.540576image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.719885image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:50.024103image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.691793image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.843148image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.084383image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.326912image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.682233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.161845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.389067image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.494909image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.586136image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.660838image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.720598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.773502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.813075image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.857081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.916458image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.166320image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.304900image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.459666image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.636320image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.823351image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:50.125863image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.785548image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.941887image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.184150image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.429644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.776966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.264256image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.480850image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.587664image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.678863image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.751161image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.811354image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.861294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.902835image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.946406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:36.012202image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.262416image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.400647image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.558405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.731040image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.926838image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:50.229097image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.880293image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.042586image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.283882image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.532360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.872277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.365016image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.575568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.681413image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.770653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.842485image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.903111image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.951721image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.993621image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.038132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.199184image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.358652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.496361image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.655276image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.827360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.029562image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:50.737311image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.975041image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.142319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.383652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.635085image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.967562image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.467308image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.668354image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.773733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.863011image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.933338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.992868image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.042509image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.084351image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.127923image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.294930image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.453356image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.591132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.753584image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.922146image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.133256image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:50.840064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.069796image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.242083image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.483951image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.738809image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.062374image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.568550image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.762104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.867507image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:23.954759image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.023099image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.083628image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.134238image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.175169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.217681image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.390164image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.549554image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.686881image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.851353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.017927image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.237706image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:50.942789image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.165534image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.342784image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.585247image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.841532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.163100image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.677257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.860835image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:21.965245image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.053451image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.118842image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.177375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.228022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.270944image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.314426image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.491319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.649294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.787598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:43.954078image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.117627image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.345939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.051499image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.265265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.448566image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.690503image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:59.949248image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.263831image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.784972image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:19.960568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.064975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.151187image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.215584image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.273118image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.323803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.367266image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.410165image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.592395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.750021image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.887315image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.057802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.218514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.455215image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.159213image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.365995image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.561263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.796249image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.056957image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.364603image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:17.893676image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.059299image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.161757image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.249501image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.311299image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.369440image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.422094image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.464570image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.505880image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.693514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.850746image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:41.987644image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.160559image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.319301image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.563491image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.267920image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.464731image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.665984image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:57.900972image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.165055image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.468854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.004384image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.161619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.265480image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.351233image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.412039image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.469196image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.523391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.564301image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.605616image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.797647image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:39.954469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.092400image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.267807image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.422600image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.675195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.379074image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.570481image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.775334image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.009672image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.276418image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.569584image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.111097image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.260359image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.363216image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.450960image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.507803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.564973image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.618673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.661039image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.701387image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:37.897704image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.054205image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.193160image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.371136image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.523937image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.783874image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.486778image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.670214image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.879113image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.115396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.384127image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.681257image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.228783image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.370108image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.472923image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.561639image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.615486image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.672845image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.727489image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.768723image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.809106image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.008697image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.166901image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.305858image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.484402image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.635200image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:48.903553image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.607478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.781915image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:55.994806image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.232056image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.502818image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.791991image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.346454image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.479815image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.581632image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.668379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.721237image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.779560image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.833178image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.875465image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:34.914394image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.116406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.277576image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.417001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.599068image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.747434image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.022264image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.725181image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.892671image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.110466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.346779image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.620529image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.891728image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.452225image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.577587image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.680366image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.766117image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.818843image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.875822image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:30.929947image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:32.971210image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.010171image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.218236image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.378339image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.517203image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.701819image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.847195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.130989image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.832927image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:53.992809image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.216213image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.451499image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.728810image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:02.998409image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.563952image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.680878image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.786186image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.870844image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:26.923649image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:28.978114image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.031675image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.073935image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.111935image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.325387image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.485115image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.625331image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.810530image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:46.953910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.246664image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:51.947328image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.101066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.327445image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.564195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.843087image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:03.106149image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.675653image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.786161image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.890890image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:24.976549image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.033404image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.080382image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.135369image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.176660image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.214656image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.433093image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.592831image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.732610image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:44.920237image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.067443image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.361357image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.062056image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.208171image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.439106image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.672513image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:00.957337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:03.216864image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:18.793371image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:20.895432image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:22.999608image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:25.084788image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:27.142670image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:29.187113image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:31.241116image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:33.282377image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:35.320378image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:38.550781image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:40.704583image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:42.844311image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:45.033931image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:47.182108image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:49.479611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:52.181045image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:54.318413image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:56.554797image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:45:58.788219image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-02-23T20:46:01.075022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2023-02-23T20:46:09.510623image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:
  • Variable_type-Variable_type : Method, Range
  • Categorical-Categorical : Cramer's V, [0,1]
  • Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
  • Numerical-Numerical : Spearman's ρ, [-1,1]
The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.
2023-02-23T20:46:09.734431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2023-02-23T20:46:09.956760image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2023-02-23T20:46:10.180283image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2023-02-23T20:46:10.369439image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2023-02-23T20:46:10.478832image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2023-02-23T20:46:03.387205image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-02-23T20:46:03.683338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

LIMIT_BALSEXEDUCATIONMARRIAGEAGEPAY_0PAY_2PAY_3PAY_4PAY_5PAY_6BILL_AMT1BILL_AMT2BILL_AMT3BILL_AMT4BILL_AMT5BILL_AMT6PAY_AMT1PAY_AMT2PAY_AMT3PAY_AMT4PAY_AMT5PAY_AMT6
0200002212422-1-1-2-23913310268900006890000
112000022226-120002268217252682327234553261010001000100002000
29000022234000000292391402713559143311494815549151815001000100010005000
35000022137000000469904823349291283142895929547200020191200110010691000
45000012157-10-10008617567035835209401914619131200036681100009000689679
550000112370000006440057069576081939419619200242500181565710001000800
650000011229000000367965412023445007542653483003473944550004000038000202391375013770
7100000222230-1-100-111876380601221-159567380601058116871542
8140000231280020001128514096121081221111793371933290432100010001000
92000013235-2-2-2-2-1-1000013007139120001300711220
LIMIT_BALSEXEDUCATIONMARRIAGEAGEPAY_0PAY_2PAY_3PAY_4PAY_5PAY_6BILL_AMT1BILL_AMT2BILL_AMT3BILL_AMT4BILL_AMT5BILL_AMT6PAY_AMT1PAY_AMT2PAY_AMT3PAY_AMT4PAY_AMT5PAY_AMT6
19923600002122500000-2279846169426688101280000700417932757000
1993290000212291-2-2-2-2-2000000000000
199420000011239-2-2-2-2-2-2-200-200-2000608000002006080000
199514000011145000022397164079941853444524543346383160016003169170017001495
1996360000111381-2-2-2-2-2000000000000
19975000022223-1-1-10-1-178007803903905000780039050018300
199812000012225220000113348110119111700838588643488802050003158393438022000
1999100000121290000-1-1944539586067782-26189574810129933205000010000071860
2000200000221280000008186586790844197041103541363250002000890006500911504
20019000022140-1-1-1-1-1-14989-8181114657133278002806225622747800

Duplicate rows

Most frequently occurring

LIMIT_BALSEXEDUCATIONMARRIAGEAGEPAY_0PAY_2PAY_3PAY_4PAY_5PAY_6BILL_AMT1BILL_AMT2BILL_AMT3BILL_AMT4BILL_AMT5BILL_AMT6PAY_AMT1PAY_AMT2PAY_AMT3PAY_AMT4PAY_AMT5PAY_AMT6# duplicates
0100001214500020071398416981595089754101921400170004006002002
11000012156222000209741933978406241964326230001502002001602
2100001222200000018773184600335763670445115002927100030010005002
31000012222000000796096498518862892935033200010005001500025002
41000012224-122200288719232989281320082132015000015002
5100001222700200070151022795609901996310182350705003703937002
610000122330000008177913196697624804968572500114510001000100015002
710000122370000228755815875408164696359231167102210360270002
810000122460022204073639461436908665267852400087102442512
910000132230000026974783890029182972994111134129847884701752